Interval-Valued Intuitionistic 2-Tuple Linguistic Bonferroni Mean Operators and Their Applications in Multi-attribute Group Decision Making

The main purposes of this paper are to propose some new Bonferroni mean (BM) operators under the interval-valued intuitionistic 2-tuple linguistic environment and apply them to multi-attribute group decision-making (MAGDM) problems. In order to aggregate correlated IVI2TLVs, we propose some new interval-valued intuitionistic 2-tuple linguistic Bonferroni mean operators, including the interval-valued intuitionistic 2-tuple linguistic Bonferroni mean (IVI2TLBM) operator, the interval-valued intuitionistic 2-tuple linguistic weighted Bonferroni mean (IVI2TLWBM) operator, and the combined interval-valued intuitionistic 2-tuple linguistic weighted Bonferroni mean (CIVI2TLWBM) operator. Furthermore, a ranking method is presented to solve MAGDM problems. Finally, a real-life application of the proposed method is given, and the sensitivity analysis and comparative analysis are carried out to verify the effectiveness and feasibility of the method.